Tower Top Daily Average
library(tidyverse)
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top <- read.csv('Tower_Top_0066_5306_0586_Full.csv')
top$Temp <- ((top$Temp - 32)*5)/9
top <- separate(top, Time, into = c('hours','minutes'))
top$hours <- as.numeric(top$hours)
top <- na.omit(top)
for (i in 1:nrow(top)) {
if (top$minutes[i] == 30) {
top$hours[i] <- top$hours[i] + 0.5
}
}
top2 <- top %>% group_by(Date, hours)
top2$Place <- "Top2"
boxplot(Temp ~ hours, data = top2, col = "salmon", main= "Boxplots of Tower Top Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")
Tower Middle Daily Average
middle <- read.csv('Tower_Middle_7433.csv')
middle <- separate(middle, Time, into = c('hours','minutes'))
middle$hours <- as.numeric(middle$hours)
middle$Temp <- ((middle$Temp - 32)*5)/9
for (i in 1:nrow(middle)) {
if (middle$minutes[i] == 30) {
middle$hours[i] <- middle$hours[i] + 0.5
}
}
middle2 <- middle %>% group_by(Date, hours)
middle2$Place <- "Middle2"
boxplot(Temp ~ hours, data = middle2, col = "green", main = "Boxplots of Tower Middle Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")
Tower Top + Tower Middle Comparison
library(plotly)
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mis <- middle %>% arrange(Date, hours)
mis$Place <- "Middle"
for (i in 1:nrow(mis)) {
if (mis$minutes[i] == 45) {
mis$hours[i] <- mis$hours[i] + 0.5
}
}
mis2 <- mis %>% distinct(Date, hours, .keep_all = T) %>% group_by(hours) %>% mutate(Average = mean(Temp, na.rm = T)) %>% slice(1)
mis3 <- top %>% arrange(Date, hours)
mis3$Place <- "Top"
for (i in 1:nrow(mis3)) {
if (mis3$minutes[i] == 45) {
mis3$hours[i] <- mis3$hours[i] + 0.5
}
}
mis4 <- mis3 %>% distinct(Date, hours, .keep_all = T) %>% group_by(hours) %>% mutate(Average = mean(Temp, na.rm = T)) %>% slice(1)
mis4$Place <- "Top"
topmiddle <- rbind(mis2, mis4)
topmiddle$hours <- as.numeric(topmiddle$hours)
plot1 <- ggplot(topmiddle, aes(hours, Average, color = Place)) + geom_smooth(aes(x = hours, y = Average), method = "lm",
formula = y ~ poly(x, 23), se = FALSE) + geom_errorbar(alpha = 0.3, aes(ymin = Average - sd(Average, na.rm = T), ymax = Average + sd(Average, na.rm = T), width = 0.2))
plot1
Tower Base Daily Average
base <- read.csv('Tower Base 4377.csv')
base$Temp <- ((base$Temp - 32)*5)/9
base <- separate(base, Time, into = c('hours','minutes'))
base$hours <- as.numeric(base$hours)
base <- na.omit(base)
for (i in 1:nrow(base)) {
if (base$minutes[i] == 30) {
base$hours[i] <- base$hours[i] + 0.5
}
}
base2 <- base %>% group_by(Date, hours)
base2$Place <- "Base2"
boxplot(Temp ~ hours, data = base2, col = "salmon", main= "Boxplots of Tower Base Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")
Plots of Tower
mis <- middle %>% arrange(Date, hours)
mis$Place <- "Middle"
mis$minutes <- as.numeric(mis$minutes)
mis$hours <- as.numeric(mis$hours)
for (i in 1:nrow(mis)) {
if (mis$minutes[i] == 45) {
mis$hours[i] <- mis$hours[i] + 0.5
}
}
mis2 <- mis %>% distinct(Date, hours, .keep_all = T) %>% group_by(hours) %>% mutate(Average = mean(Temp, na.rm = T)) %>% slice(1)
mis3 <- top %>% arrange(Date, hours)
mis3$Place <- "Top"
mis3$minutes <- as.numeric(mis3$minutes)
mis3$hours <- as.numeric(mis3$hours)
for (i in 1:nrow(mis3)) {
if (mis3$minutes[i] == 45) {
mis3$hours[i] <- mis3$hours[i] + 0.5
}
}
mis4 <- mis3 %>% distinct(Date, hours, .keep_all = T) %>% group_by(hours) %>% mutate(Average = mean(Temp, na.rm = T)) %>% slice(1)
mis4$Place <- "Top"
mis5 <- base %>% arrange(Date, hours)
mis5$Place <- "Base"
mis5$minutes <- as.numeric(mis5$minutes)
mis5$hours <- as.numeric(mis5$hours)
for (i in 1:nrow(mis5)) {
if (mis5$minutes[i] == 45) {
mis5$hours[i] <- mis5$hours[i] + 0.5
}
}
mis6 <- mis5 %>% distinct(Date, hours, .keep_all = T) %>% group_by(hours) %>% mutate(Average = mean(Temp, na.rm = T)) %>% slice(1)
mis6$Place <- "Base"
topmiddle <- rbind(mis2, mis6, mis4)
topmiddle$hours <- as.numeric(topmiddle$hours)
ggplot(topmiddle, aes(hours, Average, color = Place)) + geom_smooth(aes(x = hours, y = Average), method = "lm", formula = y ~ poly(x, 23), se = FALSE) + geom_errorbar(alpha = 0.2, aes(ymin = Average - sd(Average, na.rm = T), ymax = Average + sd(Average, na.rm = T), width = 0.2)) + geom_rect(aes(xmin = 5.75, xmax = 6.25, ymin = 20, ymax = 30),
fill = "transparent", color = "black", size = 0.5, linetype = 2) + ggtitle("Plots of Tower")
ggplotly(plot1)
library(tidyverse)
MP150 <- read.csv("MP150_5354_7432.csv")
Lago0066 <- read.csv("Lago 0066.csv")
Lago5353 <- read.csv("Lago 5353.csv")
MP150 Plot Daily Average
MP150 <- read.csv("MP150_5354_7432.csv")
MP150 <- separate(MP150, Date...Time, into = c("dates", "Time"), sep = " ")
MP150$dates <- as.Date(MP150$dates, "%m/%d/%Y")
MP150 <- separate(MP150, Time, into = c('hours','minutes'))
MP150$hours <- as.numeric(MP150$hours)
MP1502 <- MP150 %>% group_by(dates, hours)
boxplot(Temperature ~ hours, data = MP1502, col = "salmon", main= "Boxplots of MP150 Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")
Lago Plot Daily Average
Lago0066 <- read.csv("Lago 0066.csv")
Lago5353 <- read.csv("Lago 5353.csv")
Lago5353 <- Lago5353[,-1]
colnames(Lago5353) <- c("Number", "Date...Time", "Temperature", "Humidity")
colnames(Lago0066) <- c("Number", "Date...Time", "Temperature", "Humidity")
Lago <- rbind(Lago0066, Lago5353)
Lago$Temperature <- ((Lago$Temperature - 32)*5)/9
Lago <- separate(Lago, Date...Time, into = c("dates", "Time"), sep = " ")
Lago$dates <- as.Date(Lago$dates, "%m/%d/%Y")
Lago <- separate(Lago, Time, into = c('hours','minutes'))
Lago$hours <- as.numeric(Lago$hours)
Lago2 <- Lago %>% group_by(dates, hours)
boxplot(Temperature ~ hours, data = Lago2, col = "salmon", main= "Boxplots of Lago Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")
hello <- Lago2 %>% filter(dates == "2019-08-04")
Parahuaco Plot Daily Average
Parahuaco <- read.csv("Parahuaco RH.csv")
Parahuaco <- separate(Parahuaco, Date...Time, into = c("dates", "Time"), sep = " ")
Parahuaco$dates <- as.Date(Parahuaco$dates, "%m/%d/%Y")
Parahuaco <- separate(Parahuaco, Time, into = c('hours','minutes'))
Parahuaco$hours <- as.numeric(Parahuaco$hours)
boxplot(Temperature ~ hours, data = Parahuaco, col = "salmon", main= "Boxplots of Parahuaco Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")
GP Plot Daily Average
GP <- read.csv("GP RH.csv")
GP <- GP[,-1]
GP <- separate(GP, Date...Time, into = c("dates", "Time"), sep = " ")
GP$dates <- as.Date(GP$dates, "%m/%d/%Y")
GP <- separate(GP, Time, into = c('hours','minutes'))
GP$hours <- as.numeric(GP$hours)
GP2 <- GP %>% group_by(dates, hours)
boxplot(Temperature ~ hours, data = GP, col = "salmon", main= "Boxplots of GP Temperatures", xlab = "Hours from Midnight (2019-07-26)", ylab = "Temperature in Celcius")
Murcialago (Rest) Daily Average
Murcialago <- read.csv("Murcialago5306.csv")
Murcialago <- separate(Murcialago, Date...Time, into = c("dates", "Time"), sep = " ")
Murcialago$dates <- as.Date(Murcialago$dates, "%m/%d/%Y")
Murcialago <- separate(Murcialago, Time, into = c('hours','minutes'))
Murcialago$hours <- as.numeric(Murcialago$hours)
Murcialago2 <- Murcialago %>% group_by(dates, hours)
boxplot(Temperature ~ hours, data = Murcialago2, col = "salmon", main= "Boxplots of Murcialago Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")
Parahuaco (Rest) Daily Average
Parahuaco <- read.csv("Parahuaco RH.csv")
Parahuaco <- separate(Parahuaco, Date...Time, into = c("dates", "Time"), sep = " ")
Parahuaco$dates <- as.Date(Parahuaco$dates, "%m/%d/%Y")
Parahuaco <- separate(Parahuaco, Time, into = c('hours','minutes'))
Parahuaco$hours <- as.numeric(Parahuaco$hours)
Parahuaco2 <- Parahuaco %>% group_by(dates, hours)
boxplot(Temperature ~ hours, data = Parahuaco2, col = "salmon", main= "Boxplots of Parahuaco Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")
Danta (Rest) Daily Average
dataset <- read.csv("Denta Region RH.csv")
dataset <- dataset[,-1]
colnames(dataset) <- c("Number", "Date...Time", "Temperature", "Humidity")
Danta <- separate(dataset, Date...Time, into = c("dates", "Time"), sep = " ")
Danta$dates <- as.Date(Danta$dates, "%m/%d/%Y")
Danta <- separate(Danta, Time, into = c('hours','minutes'))
Danta$hours <- as.numeric(Danta$hours)
Danta2 <- Danta %>% group_by(dates, hours)
boxplot(Temperature ~ hours, data = Danta2, col = "salmon", main= "Boxplots of Danta Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")
Titi Cabin (Sleep) Daily Average
dataset <- read.csv("TitiCabin9223.csv")
dataset <- separate(dataset, Date...Time, into = c("dates", "Time"), sep = " ")
dataset$dates <- as.Date(dataset$dates, "%m/%d/%Y")
dataset <- separate(dataset, Time, into = c('hours','minutes'))
dataset$hours <- as.numeric(dataset$hours)
dataset2 <- dataset %>% group_by(dates, hours)
boxplot(Temperature ~ hours, data = dataset2, col = "salmon", main= "Boxplots of Titi Cabin Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")
Titi Trail (Sleep) Daily Average
dataset <- read.csv("TitiTrail2115.csv")
dataset <- separate(dataset, Date...Time, into = c("dates", "Time"), sep = " ")
dataset$dates <- as.Date(dataset$dates, "%m/%d/%Y")
dataset <- separate(dataset, Time, into = c('hours','minutes'))
dataset$hours <- as.numeric(dataset$hours)
dataset2 <- dataset %>% group_by(dates, hours)
boxplot(Temperature ~ hours, data = dataset, col = "salmon", main= "Boxplots of Titi Trail Temperatures", xlab = "Hours from Midnight", ylab = "Temperature in Celcius")
